TY - GEN
T1 - Predicting Student Achievement before Final Exam
T2 - 2nd International Conference on Information Technology and Education, ICIT and E 2022
AU - Ma'sum, M. Anwar
N1 - Funding Information:
ACKNOWLEDGMENT This work is supported by the "Program Pendanaan Perancangan Dan Pengembangan Purwarupa" (P5) Grant from the Directorate of Innovation and Science Techno Park (DISTP) Universitas Indonesia 2020-2021 led by the author of the paper.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - An early prediction of student achievement on a course is an important instrument to forecast student accomplishment in the learning process. Besides, it is also functioned to help the students who might be failed. In this study, we proposed a regression-based early prediction of student achievement. The prediction system utilized the data from last semester to predict the final score of the students in the current semester. The proposed approach was tested in two scenarios. First, predicting the final score directly and the second is predicting the final exam score continued by final score calculation by using predefined formula. The experiment result shows that overall, the second scenario produces a better result than the first scenario. The SVR-Linear achieves the highest performance in the first scenario with 3.56 MAE, 0.048 MAPE, 17.63 MSE, 4.2 RMSE, and 0.781 R-squared. SVR-RBF achieves the highest performance in the second scenario with 3.0 MAE, 0.043 MAPE, 13.05 MSE, 3.6 RMSE, and 0.838 R-squared.
AB - An early prediction of student achievement on a course is an important instrument to forecast student accomplishment in the learning process. Besides, it is also functioned to help the students who might be failed. In this study, we proposed a regression-based early prediction of student achievement. The prediction system utilized the data from last semester to predict the final score of the students in the current semester. The proposed approach was tested in two scenarios. First, predicting the final score directly and the second is predicting the final exam score continued by final score calculation by using predefined formula. The experiment result shows that overall, the second scenario produces a better result than the first scenario. The SVR-Linear achieves the highest performance in the first scenario with 3.56 MAE, 0.048 MAPE, 17.63 MSE, 4.2 RMSE, and 0.781 R-squared. SVR-RBF achieves the highest performance in the second scenario with 3.0 MAE, 0.043 MAPE, 13.05 MSE, 3.6 RMSE, and 0.838 R-squared.
KW - final exam
KW - prediction
KW - regression
KW - student achievement
UR - http://www.scopus.com/inward/record.url?scp=85129960035&partnerID=8YFLogxK
U2 - 10.1109/ICITE54466.2022.9759885
DO - 10.1109/ICITE54466.2022.9759885
M3 - Conference contribution
AN - SCOPUS:85129960035
T3 - Proceedings - 2022 2nd International Conference on Information Technology and Education, ICIT and E 2022
SP - 424
EP - 428
BT - Proceedings - 2022 2nd International Conference on Information Technology and Education, ICIT and E 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 22 January 2022
ER -